Abstract

In recent years, architectural design with dynamic facade has been more widely introduced as a solution for building environmental issues. From the morphological point of view, this paper attempts to explore the performance otherness of different dynamic typologies during the optimisation of the design process. Take high-rise office building in the tropical region as an example, The two common typologies of rotation and folding are compared and discussed by parameter simulation method with 36 cases in terms of scale, motion and transmittance to find the optimal trade-off between minimising energy demand for cooling and lighting and maximising daylight comfort.
The results of the study show that the energy demand for cooling and lighting can be reduced by 19%- 24% through dynamic façade while folding typology has better performance in energy conservation in all the three orientations. For daylighting, the average daylight comfort area has an increase of 5%-14%, while the value of rotation typology is higher than folding typology. Furthermore, Motion has an influence on the daylight and energy performance except for energy demand of rotation typology. Differently, Transmittance is related to both performances except daylight of rotation typology. This study provides a performance-based approach to dynamic facade selection. A designer could make the decision not only from aesthetic considerations but also combine them to get higher performance.

Abstract

Compressed Air Energy Storage (CAES) is one of the promising methods to store the surplus solar and wind energy in a grid scale. In this study, we used a non-isothermal multiphase flow simulator to model a field-scale study of a novel CAES by storing the compressed air in aquifer. The primary results show that the model is capability of modeling dynamics of pressure induced by air injection rates. The model was successful to model the well head pressure changes during the bubble development stage. This study suggests that further works shall be carried out to validate the model by simulating the injection-withdrawal cycle’s experiments, as well as to investigate key factors affecting storage and thermal efficiency of compressed air in porous rock reservoirs.

Abstract

As a new entrant of fuel market, biofuel refuelling stations are faced with the keen competition from existing petrol stations. The optimal planning of biofuel refuelling stations strongly affects the profit of biofuel company. However, there are few studies to deal with this issue. This paper develops a bilevel game-theoretic framework that consists of an upper-level model for the petroleum company and a lower-level model for the biofuel company. The mutual restraint relations among biofuel company, petroleum company and the market are all formulated into the models. Finally, the proposed method is validated by a real-world case in China.

Abstract

Aiming at the economical and safe operation of distribution networks with high permeability of distributed wind power generations, a dynamic reconfiguration method based on voltage fluctuation deviation is proposed. Firstly, in order to reduce the continuous action of the switch in a short time, a single switch operation cost model is constructed and introduced into the distribution network dynamic reconfiguration model in the form of a similar penalty function. Then, the voltage fluctuation deviation index of the distribution network node is proposed. It can characterize the development trend of the overall state of the distribution network. According to the magnitude and time series distribution of the voltage fluctuation deviation value, the reconstructed time division result can be obtained intuitively. Finally, the speed and location update mechanism has been improved to overcome the limitations of the traditional binary particle swarm reconfiguration. Results of calculation example show that the proposed method is efficient and effective.

Abstract

The non-technical losses in Electric Sector are all the wastes of energy that occurs in the electricity distribution grid because of commercials and manageable aspects. For example, this losses are higher associated with electric theft. To incentive the concessionaires to have a good performance in combat these losses, there is a regulatory treatment that imposes some targets for this issue. In Brazil, the regulatory framework adopt a benchmark model to determine the target. In this model, the regulator uses a regulator econometric approach with socioeconomic data to subsidize the comparison between companies based on the complexity of each concession area. This article execute a critical econometric analysis of this methodology. For this, the article discuss the effectiveness of the model based on econometric test of estimations and residuals. Moreover, there is a specific analysis for the specification of variables and for the autocorrelations in the model. In the end, the paper demonstrate the weaknesses of the model to represent the reality of fighting against losses in the sector. As a result, there are contests about the choice of this type of model and the biases of omitted variables.

Abstract

This paper presented a torque distribution strategy based on linear time-varying quadratic programming (LTV-QP) for yaw stability control of all-wheelindependent- drive electric vehicles. A two-degree-offreedom vehicle dynamic model was established to figure out the desired vehicle states including sideslip angle of the centroid of vehicle and the yaw moment, which was used as the reference signal of the LTV-QP controller. However, the influence of the time-varying steering angle was generally not taken into account. A QP-based torque distribution strategy is put forward to reduce the yaw rate error caused by them. The proposed strategy is evaluated in Matlab/Simulink to track the reference yaw moment and optimize the torque distribution. The results indicate that the LTV-QP controller can effectively distribute the torques of four in-wheel motors and significantly improve the vehicle yaw stability.

Abstract

Large scale utilization of solar energy has become an inevitable trend of an energy-efficient and environment-friendly society. A two-stage robust allocation model of solar energy equipments in district integrated energy systems is proposed in this paper with the uncertainty of solar irradiance and operating constraints of energy networks. To improve the solvability, the above non-convex non-linear model is converted to a 0-1 mixed integer second-order cone problem. The validity of the model is verified by typical cases.

Abstract

Ion diffusivity is one of the most important properties in the electrolyte for batteries, as poor mass transport can cause large performance losses during operation. Therefore, the understanding of the relations between diffusivity and electrolyte conditions, such as compositions and concentrations, is crucial for designing proper electrolytes for batteries. In this paper, we investigate the diffusion of zinc ions in ZnCl2- DMSO electrolytes using microfluidics with fluorescence microscopy. It is found that the diffusion of zinc ions in the electrolytes is sensitive to concentration variations.

Abstract

In metal-air batteries, heteroatom-doped carbon catalysts have been widely regarded as promising substitutes for Pt-based catalysts for enhancing oxygen reduction reaction (ORR) performance owing to their excellent catalytic activity and low cost. Sulfur (S) is a potential heteroatom dopant. However, its large atomic radius causes limitations, such as edge-selective doping and low doping amount. Herein, we report a successful fabrication of edge-enriched S-doped carbon nanoflakes (ESCNs) with S doping amount as high as 6.04 at% by chemical vapor deposition (CVD) method using thiophene as carbon/sulfur source and basic magnesium carbonate (BMC) nanoflake as template. The as-obtained ESCNs are highly porous with well-crystallized graphite layers on the edge and possess a large specific surface area of 1,306 m2 g-1, resulting in remarkable ORR catalytic performance under alkaline condition. The ORR yields a high current density of 7.0 mA cm-2 at -0.03 V (vs. RHE) and outstanding durability. When applied in zinc-air batteries, the as-developed ESCNs demonstrate superior electrochemical performance under different discharge current densities.

Abstract

With the increase of residential energy consumption, its proportion in primary energy consumption is higher and higher. Accurate prediction of residential electricity consumption is the premise of rational residential energy management. In this paper, a novel multi-step prediction model using particle swarm optimization (PSO), Holt-Winter (HW) method, and extreme learning machine (ELM) network is proposed for forecasting household power consumption. The HW model optimized by PSO is the main predictor and used to deal with the periodicity and seasonality of household electricity load. ELM model is introduced as the correction predictor to predict the prediction error of HW, so as to improve the prediction accuracy. The experimental results show that the PSO-HW-ELM model has higher prediction accuracy and better stability compared with the single HW and ELM model.